salim G shaikh

@aiktc.ac.in

Assistant Professor, Department of Computer Engineering.
AIKTC, Computer Engineering

salim G shaikh


               Download Compact PDF  
https://researchid.co/shaikhsg2

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Computer Engineering, Artificial Intelligence
15

Scopus Publications

98

Scholar Citations

6

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • A Hybrid Feature Selection Gradient Recurrent Neural Network (HFSGRNN) Model for Rainfall Prediction in India Regions
    International Journal of Intelligent Engineering and Systems, 2024
    In current studies, India is a farming country, and the accomplishment or disappointment of the crop mainly depends on the country's rainfall design.Generally, India's farming production is primarily based on the nature of the precipitation of the rainy season rainfall.The rainy season is the primary source of water in India.Regular rainfall forecasting is the primary source for crop development.Several analyses have defined the direct effect of rainwater on harvests.The main motive of this research work is proper and early rainfall prediction, which is helpful to people who live in northeast regions inclined to natural disasters like floods, etc.It helps agriculture with decision-making in their crop and water management (WM) using extensive dataset analysis that generates maximum terms of production for farmers and profits.This proposed work introduced an improved rainfall forecasting framework, a hybrid feature selection gradient-based RNN (HFSGRNN) model with an RNN algorithm.The research uses the HFSGRNN model steps, such as initial data preprocessing steps, which are used for forecasting rainfall, handling missing value outliers, and typecasting the rainfall dataset collected from the government site.After that, an HFSGRNN method is implemented to select the valuable using stochastic gradient descent (SGD) and optimal solutions calculated by particle swarm optimization (PSO) from the preprocessed data.The hybrid optimized feature sets are fed to the rainfall forecasting of the RNN classifier.Lastly, the valuable feature sets are forecasted using decision-making, and the simulation outcome shows that the research approach performed better in rainfall forecasting.The simulation results define that the HFSGRNN model delivered the minimum value of Root means square error (RMSE= 0.10) and maximum value of accuracy rate (acc = 98.1%) compared with existing methods, such as logistic regression (LR), Long Short Term -Convolutional Neural Network (LSTM-CNN), etc.The outcomes of the research analysis will help the farmers accept efficient modeling methods for forecasting long-term seasonal rainfall.
  • Intelligent rainfall forecasting model: heuristic assisted adaptive deep temporal convolutional network with optimal feature selection
    Nishant Nilkanth Pachpor, B. Suresh Kumar, Prakash S. Prasad, Salim G. Shaikh
    International Journal of Intelligent Information and Database Systems, 2024
    A deep learning technology is adopted to predict seasonal rainfall efficiently. Various rainfall data are collected from the internet. A deep feature extraction is done by autoencoder. Further, the deep extracted features are provided to the optimal feature selection phase, where the weights are optimised by utilising the developed modified attack power-based sail fish-hybrid leader optimisation (MAP-SFHLO). Then, the selected optimal features are provided as input to the prediction stage, and the prediction is done using the enhanced atrous-based adaptive deep temporal convolutional network (EA-ADTCN) along with the aid of the developed MAP-SFHLO algorithm to offer an effective prediction rate as the final outcome. Throughout the analysis, the performance of the developed model shows 5.2% and 6.0% regarding MAE and RMSE metrics. Thus, the suggested system performs more accurately in terms of accuracy rate in predicting rainfall than conventional techniques.
  • Hybrid machine learning method for classification and recommendation of vector-borne disease
    Salim Gulab Shaikh, Billakurthi Suresh Kumar, Geetika Narang, Nishant Nilkanth Pachpor
    Journal of Autonomous Intelligence, 2024
    Vector-borne diseases (VBD) are a class of infectious illnesses that are transmitted to humans and animals through the bites of arthropod vectors, such as mosquitoes, ticks, and fleas. These diseases are caused by a variety of pathogens, including bacteria, viruses, and parasites, and are a significant global public health concern. Vector-borne diseases are prevalent in many parts of the world, particularly in tropical and subtropical regions, where the vectors thrive. This research has contributed by constructing a hybrid machine learning based prediction model, which helps to discover patients who are infected by vector-borne disease at an earlier stage and also helps with the categorization and diagnosis of severe vector-borne disease. The model that has been proposed is made up of units: data conversion, data preprocessing, normalization, extraction of feature, splitting of dataset, and classification and prediction unit. The fact that the suggested prediction model is capable of identifying vector-borne disease in its early phases as well as categorizing the kind of disease using the medical report of a sufferer is one of the innovative aspects of the model. The 7 distinct conventional machine learning and single hybrid machine learning (HML) are applied for classification and Recurrent Neural Network (RNN) based reinforcement learning are utilized for recommendation. In order to evaluate the effectiveness of the system that’s been proposed, a number of tests were carried out. A dataset consisting of 1539 different cases of a disease transmitted by vectors has been collected. The 11 common vector-borne diseases namely malaria, dengue, Japanese encephalitis, kala-azar and chikungunya were taken for experimental evaluation. The performance accuracy of the proposed prediction model has been measured at 98.76%, which assists the healthcare team in making decisions on a timely basis and ultimately helps to save the patient’s lives. The final phase system provides the recommendation for those classifiers resulting in four different classes such as normal, mild, moderate and severe respectively. The recommendation is also demonstrating future direction for cure of vector borne disease.
  • Exploring Medical Diagnosis Using Vision Transformer And CNN
    Saqlain Kalokhe, Fahad Khan, Salim Shaikh, Nusrat Jahan
    2024 2nd Dmiher International Conference on Artificial Intelligence in Healthcare Education and Industry Idicaiei 2024, 2024
    This research aims to conduct a comparative analysis of Vision Transformer (ViT) and Convolutional Neural Network (CNN) models for detecting four prevalent diseases: eye diseases, lung diseases, skin diseases, and heart diseases. The primary goal is to identify the most suitable and efficient model for each disease, taking into account their unique characteristics and diagnostic requirements. Through a meticulous evaluation and comparison of the performance of various ViT and CNN models for each illness, this study endeavors to offer valuable insights into the optimal utilization of these advanced technologies in disease detection. The comprehensive analysis presented in this paper is intended to contribute to the progress of medical imaging and potentially enhance diagnostic precision and efficacy in healthcare.
  • G2OCR: Integrating Speech Recognition and Optical Character Recognition(OCR) for Automated Transcription of Gujarati Audio-Visual Content
    Jawad Deshmukh, Sharique Shah, Asif Shaikh, Ashfan Bargir, Salim Shaikh
    Proceedings of the 4th International Conference on Ubiquitous Computing and Intelligent Information Systems Icuis 2024, 2024
    The rapid boom of virtual content in neighborhood languages together with Gujarati has created demanding situations in accessibility and searchability. A sizable part of this content material, in particular audio and video, stays inaccessible to people with listening to impairments due to the lack of transcriptions. additionally, the absence of a searchable layout limits discoverability. G2OCR objectives is to provide a solution through transcribing Gujarati audio-visible content via a gadget that leverages speech recognition and optical individual recognition (OCR) technology. This approach enhances accessibility and preserves the language via making content more searchable. constructing on earlier studies, G2OCR integrates superior strategies to supply a robust device ideal for a selection of environments.
  • Computer Vision Advancement with Vision Transformers: A Comprehensive Review
    Saqlain Kalokhe, Fahad Khan, Aliasgar Shaikh, Ebad Ansari, Salim Shaikh, Nusrat Jahan
    Proceedings 2024 5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks Icicv 2024, 2024
    The adoption of vision transformers for image recognition tasks has exploded in recent years, leading to the coexistence of numerous transformer variants. However, the lack of a comprehensive analysis and comparison of these models has left researchers and practitioners unsure of the best options for their applications. The subtleties of different vision transformers are explored, and a thorough comparison is carried out in this study. The research is motivated by the vision transformers' increasingly important role in contemporary computer vision, and it aims to contribute to the advancement of the state-of-the-art in image recognition. By outlining the distinctive qualities, benefits, and drawbacks of these models, the community is provided with a useful resource that simplifies the decision-making process for researchers and practitioners. Ultimately, the goal is to pave the way for more accurate, efficient, and impactful image recognition solutions.
  • Development of optimized ensemble classifier for dengue fever prediction and recommendation system
    Mr. Salim G. Shaikh, Dr. B. SureshKumar, Dr.Geetika Narang
    Biomedical Signal Processing and Control, 2023
  • Diagnosis of Vector Borne Disease using Various Machine Learning Techniques
    International Journal of Intelligent Systems and Applications in Engineering, 2023
  • Several Classification and Recommendations Methods Used in Dengue Fever Prediction System
    Salim G. Shaikh, B. Suresh Kumar, Geetika Narang, N.N. Pachpor
    2023 International Conference on Integration of Computational Intelligent System Icicis 2023, 2023
    Mosquitos influence dengue fever, and the dengue virus is a universal community health issue worldwide. An analysis and prediction are required to resolve the effects of the dengue virus in communities. The main motive of this article is to recognize the classification or recommendation methods based on machine learning (ML) and deep learning (DL) for predicting and detecting dengue fever. The classification methods such as SVM, KNN, DT, and naïve bayes are used to perform experimental results. In this article, a comparison of these methods is executed, and SVM achieves a better accuracy rate. This method is highest accurate and suitable for predicting the dengue virus. The naïve bays is an effective method for better performance with less time-consuming. This method takes 0.01 seconds and reduces the probability of errors. The techniques like DT, KNN, and naïve Bayes provide 55.5%, 96%, and 72% accuracy, respectively. The SVM, DT, and naïve bayes consumed the time of 0.16sec, 0.05sec, and 0.01sec, respectively.
  • Several Categories of the Classification and Recommendation Models for Dengue Disease: A Review
    Salim G. Shaikh, B. Suresh Kumar, Geetika Narang
    Lecture Notes in Networks and Systems, 2022
  • Recommender system for health care analysis using machine learning technique: a review
    Salim G. Shaikh, B. Suresh Kumar, Geetika Narang
    Theoretical Issues in Ergonomics Science, 2022
  • Different Nature-Inspired Optimization Models Using Heavy Rainfall Prediction: A Review
    Nishant N. Pachpor, B. Suresh Kumar, Prakash S. Parsad, Salim G. Shaikh
    Lecture Notes in Networks and Systems, 2022
  • Scientific Study of Asphalt Road Surface Distress and their Role in the Design of Flexible Pavements
    Salim G. Shaikh, Dinesh U Mahajan, Mohammad Nubairshah S. Shaikh, Abhijeet P. Wadekar
    International Journal of Engineering Trends and Technology, 2022
  • Systematic Evaluation and Analysis of Bituminous Road Pavement Failure
    Salim G Shaikh, Abhijeet P Wadekar
    Journal of Physics Conference Series, 2021
  • Role of nanotechnology in bituminous road pavements
    S G Shaikh, M D R Khan, A M Bhalkar, A P Wadhekar
    Journal of Physics Conference Series, 2020

RECENT SCHOLAR PUBLICATIONS

  • Web Driven Health Insights: An Al-Powered Recommendation System for Optimized Patient Care
    A Shaikh¹, S Shaikh, T Maktum, V Gotarane
    Proceedings of the MULTINOVA: First International Conference on Artificial … , 2025
    2025
  • Simhastha Ujjain Smart Policing: Using Communication and Face Recognition Technology to Improve Public Safety
    A Shaikh¹, S Shaikh, T Khan, S Sayyed
    Proceedings of the MULTINOVA: First International Conference on Artificial … , 2025
    2025
  • Studying and exploring various machine learning methods employed in rainfall forecasting prediction
    NN Pachpor, BS Kumar, PS Prasad, SG Shaikh
    Sustainable Smart Technology Businesses in Global Economies, 513-527 , 2025
    2025
    Citations: 1
  • G2OCR: Integrating Speech Recognition and Optical Character Recognition (OCR) for Automated Transcription of Gujarati Audio-Visual Content
    J Deshmukh, S Shah, A Shaikh, A Bargir, S Shaikh
    2024 4th International Conference on Ubiquitous Computing and Intelligent … , 2024
    2024
    Citations: 1
  • Exploring Medical Diagnosis Using Vision Transformer And CNN
    S Kalokhe, F Khan, S Shaikh, N Jahan
    2024 2nd DMIHER International Conference on Artificial Intelligence in … , 2024
    2024
    Citations: 1
  • Optimal Keyword Selection by Hybrid Optimization with Itemset Mining for Text Summarization in Biomedical Sector
    N Pachpor, S Shaikh, S Misal, A Brahme
    IJCRT Research Journal| UGC Approved and UGC Care Journal| Scopus Indexed … , 2024
    2024
    Citations: 2
  • Enhanced Fake News Detection with the Aid of Improved Spider Monkey Optimization-Based Optimal Feature Selection and Deep Neural Network
    N Pachpor, S Shaikh, M Ansari
    IJCRT Research Journal| UGC Approved and UGC Care Journal| Scopus Indexed … , 2024
    2024
  • Computer Vision Advancement with Vision Transformers: A Comprehensive Review
    S Kalokhe, F Khan, A Shaikh, E Ansari, S Shaikh, N Jahan
    2024 5th International Conference on Intelligent Communication Technologies … , 2024
    2024
    Citations: 2
  • A Hybrid Feature Selection Gradient Recurrent Neural Network (HFSGRNN) Model for Rainfall Prediction in India Regions.
    NN Pachpor, BS Kumar, PS Prasad, SG Shaikh
    International Journal of Intelligent Engineering & Systems 17 (2) , 2024
    2024
    Citations: 6
  • Association Rule Mining and Information Retrieval Using Stemming and Text Mining Techniques
    A Brahme, S Shaikh, S Lokare, S Kulkarni, S Mundhe, AA Jadhav, ...
    2024
    Citations: 2
  • Intelligent rainfall forecasting model: heuristic assisted adaptive deep temporal convolutional network with optimal feature selection
    NN Pachpor, BS Kumar, PS Prasad, SG Shaikh
    International Journal of Intelligent Information and Database Systems 16 (4 … , 2024
    2024
    Citations: 1
  • Original Research Article Hybrid machine learning method for classification and recommendation of vector-borne disease
    SG Shaikh, BS Kumar, G Narang, NN Pachpor
    Journal of Autonomous Intelligence 7 (2) , 2024
    2024
    Citations: 10
  • Several Classification and Recommendations Methods Used in Dengue Fever Prediction System
    SG Shaikh, BS Kumar, G Narang, NN Pachpor
    2023 International Conference on Integration of Computational Intelligent … , 2023
    2023
    Citations: 1
  • Development of optimized ensemble classifier for dengue fever prediction and recommendation system
    MSG Shaikh, B SureshKumar, G Narang
    Biomedical Signal Processing and Control 85, 104809 , 2023
    2023
    Citations: 21
  • ATTENDANCE SYSTEM USING FACE RECOGNITION AND RASPBERRY PI – REVIEW
    PSGS Ismail Mujahid Mukadam, Ansari Mohammed Sajjad ,Shaikh Fuzail Shahnawaz
    International Journal of IOT and Data Science (IJIDS) 1 (1), pp-1-6 , 2023
    2023
    Citations: 1
  • Diagnosis of vector borne disease using various machine learning techniques
    SG Shaikh, BS Kumar, G Narang, NN Pachpor
    International Journal of Intelligent Systems and Applications in Engineering … , 2023
    2023
    Citations: 8
  • Recommender system for health care analysis using machine learning technique: A review
    SG Shaikh, B Suresh Kumar, G Narang
    Theoretical Issues in Ergonomics Science 23 (5), 613-642 , 2022
    2022
    Citations: 22
  • Different Nature-Inspired Optimization Models Using Heavy Rainfall Prediction: A Review
    NN Pachpor, B Suresh Kumar, PS Parsad, SG Shaikh
    Intelligent Sustainable Systems: Proceedings of ICISS 2022, 761-775 , 2022
    2022
    Citations: 1
  • Different Nature-Inspired Optimization Models Using Heavy Rainfall Prediction: A Review
    SGS Nishant N. Pachpor , Dr. B. Suresh Kumar, Dr. Prakash S Parsad
    5th International Conference on Intelligent Sustainable Systems-Springer … , 2022
    2022
  • Several Categories of the Classification and Recommendation Models For Dengue Disease: A Review
    SG Shaikh, DBS Kumar, DG Narang
    5th International Conference on Intelligent Sustainable Systems-Springer … , 2022
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • Recommender system for health care analysis using machine learning technique: A review
    SG Shaikh, B Suresh Kumar, G Narang
    Theoretical Issues in Ergonomics Science 23 (5), 613-642 , 2022
    2022
    Citations: 22
  • Development of optimized ensemble classifier for dengue fever prediction and recommendation system
    MSG Shaikh, B SureshKumar, G Narang
    Biomedical Signal Processing and Control 85, 104809 , 2023
    2023
    Citations: 21
  • Wearable health monitoring system for babies
    S Dhumal, N Kumbhar, A Tak, SG Shaikh
    International Journal of Computer Engineering & Technology (IJCET) 7 (2), 15-23 , 2016
    2016
    Citations: 14
  • Original Research Article Hybrid machine learning method for classification and recommendation of vector-borne disease
    SG Shaikh, BS Kumar, G Narang, NN Pachpor
    Journal of Autonomous Intelligence 7 (2) , 2024
    2024
    Citations: 10
  • Diagnosis of vector borne disease using various machine learning techniques
    SG Shaikh, BS Kumar, G Narang, NN Pachpor
    International Journal of Intelligent Systems and Applications in Engineering … , 2023
    2023
    Citations: 8
  • A Hybrid Feature Selection Gradient Recurrent Neural Network (HFSGRNN) Model for Rainfall Prediction in India Regions.
    NN Pachpor, BS Kumar, PS Prasad, SG Shaikh
    International Journal of Intelligent Engineering & Systems 17 (2) , 2024
    2024
    Citations: 6
  • Secure access of RFID system
    SG Shaikh, DN Shankar
    International Journal of Scientific & Engineering Research 3 (8) , 2012
    2012
    Citations: 4
  • Optimal Keyword Selection by Hybrid Optimization with Itemset Mining for Text Summarization in Biomedical Sector
    N Pachpor, S Shaikh, S Misal, A Brahme
    IJCRT Research Journal| UGC Approved and UGC Care Journal| Scopus Indexed … , 2024
    2024
    Citations: 2
  • Computer Vision Advancement with Vision Transformers: A Comprehensive Review
    S Kalokhe, F Khan, A Shaikh, E Ansari, S Shaikh, N Jahan
    2024 5th International Conference on Intelligent Communication Technologies … , 2024
    2024
    Citations: 2
  • Association Rule Mining and Information Retrieval Using Stemming and Text Mining Techniques
    A Brahme, S Shaikh, S Lokare, S Kulkarni, S Mundhe, AA Jadhav, ...
    2024
    Citations: 2
  • Studying and exploring various machine learning methods employed in rainfall forecasting prediction
    NN Pachpor, BS Kumar, PS Prasad, SG Shaikh
    Sustainable Smart Technology Businesses in Global Economies, 513-527 , 2025
    2025
    Citations: 1
  • G2OCR: Integrating Speech Recognition and Optical Character Recognition (OCR) for Automated Transcription of Gujarati Audio-Visual Content
    J Deshmukh, S Shah, A Shaikh, A Bargir, S Shaikh
    2024 4th International Conference on Ubiquitous Computing and Intelligent … , 2024
    2024
    Citations: 1
  • Exploring Medical Diagnosis Using Vision Transformer And CNN
    S Kalokhe, F Khan, S Shaikh, N Jahan
    2024 2nd DMIHER International Conference on Artificial Intelligence in … , 2024
    2024
    Citations: 1
  • Intelligent rainfall forecasting model: heuristic assisted adaptive deep temporal convolutional network with optimal feature selection
    NN Pachpor, BS Kumar, PS Prasad, SG Shaikh
    International Journal of Intelligent Information and Database Systems 16 (4 … , 2024
    2024
    Citations: 1
  • Several Classification and Recommendations Methods Used in Dengue Fever Prediction System
    SG Shaikh, BS Kumar, G Narang, NN Pachpor
    2023 International Conference on Integration of Computational Intelligent … , 2023
    2023
    Citations: 1
  • ATTENDANCE SYSTEM USING FACE RECOGNITION AND RASPBERRY PI – REVIEW
    PSGS Ismail Mujahid Mukadam, Ansari Mohammed Sajjad ,Shaikh Fuzail Shahnawaz
    International Journal of IOT and Data Science (IJIDS) 1 (1), pp-1-6 , 2023
    2023
    Citations: 1
  • Different Nature-Inspired Optimization Models Using Heavy Rainfall Prediction: A Review
    NN Pachpor, B Suresh Kumar, PS Parsad, SG Shaikh
    Intelligent Sustainable Systems: Proceedings of ICISS 2022, 761-775 , 2022
    2022
    Citations: 1
  • Web Driven Health Insights: An Al-Powered Recommendation System for Optimized Patient Care
    A Shaikh¹, S Shaikh, T Maktum, V Gotarane
    Proceedings of the MULTINOVA: First International Conference on Artificial … , 2025
    2025
  • Simhastha Ujjain Smart Policing: Using Communication and Face Recognition Technology to Improve Public Safety
    A Shaikh¹, S Shaikh, T Khan, S Sayyed
    Proceedings of the MULTINOVA: First International Conference on Artificial … , 2025
    2025
  • Enhanced Fake News Detection with the Aid of Improved Spider Monkey Optimization-Based Optimal Feature Selection and Deep Neural Network
    N Pachpor, S Shaikh, M Ansari
    IJCRT Research Journal| UGC Approved and UGC Care Journal| Scopus Indexed … , 2024
    2024